{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Scaling to Minimum and Maximum values - MinMaxScaling\n",
    "\n",
    "Minimum and maximum scaling squeezes the values between 0 and 1. It subtracts the minimum value from all the observations, and then divides it by the value range:\n",
    "\n",
    "X_scaled = (X - X.min / (X.max - X.min)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.datasets import fetch_california_housing\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# the scaler - for min-max scaling\n",
    "from sklearn.preprocessing import MinMaxScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MedInc</th>\n",
       "      <th>HouseAge</th>\n",
       "      <th>AveRooms</th>\n",
       "      <th>AveBedrms</th>\n",
       "      <th>Population</th>\n",
       "      <th>AveOccup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.3252</td>\n",
       "      <td>41.0</td>\n",
       "      <td>6.984127</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>322.0</td>\n",
       "      <td>2.555556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.3014</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6.238137</td>\n",
       "      <td>0.971880</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>2.109842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.2574</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.288136</td>\n",
       "      <td>1.073446</td>\n",
       "      <td>496.0</td>\n",
       "      <td>2.802260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.6431</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.817352</td>\n",
       "      <td>1.073059</td>\n",
       "      <td>558.0</td>\n",
       "      <td>2.547945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.8462</td>\n",
       "      <td>52.0</td>\n",
       "      <td>6.281853</td>\n",
       "      <td>1.081081</td>\n",
       "      <td>565.0</td>\n",
       "      <td>2.181467</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MedInc  HouseAge  AveRooms  AveBedrms  Population  AveOccup\n",
       "0  8.3252      41.0  6.984127   1.023810       322.0  2.555556\n",
       "1  8.3014      21.0  6.238137   0.971880      2401.0  2.109842\n",
       "2  7.2574      52.0  8.288136   1.073446       496.0  2.802260\n",
       "3  5.6431      52.0  5.817352   1.073059       558.0  2.547945\n",
       "4  3.8462      52.0  6.281853   1.081081       565.0  2.181467"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the California House price data from Scikit-learn\n",
    "X, y = fetch_california_housing(return_X_y=True, as_frame=True)\n",
    "\n",
    "# Remove 2 variables:\n",
    "X.drop(labels=[\"Latitude\", \"Longitude\"], axis=1, inplace=True)\n",
    "\n",
    "# display top 5 rows\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((14448, 6), (6192, 6))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's separate the data into training and testing sets\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "    X,\n",
    "    y,\n",
    "    test_size=0.3,\n",
    "    random_state=0,\n",
    ")\n",
    "\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up the scaler\n",
    "scaler = MinMaxScaler().set_output(transform=\"pandas\")\n",
    "\n",
    "# fit the scaler to the train set, it will learn the parameters\n",
    "scaler.fit(X_train)\n",
    "\n",
    "# transform train and test sets\n",
    "X_train_scaled = scaler.transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.50001000e+01, 5.20000000e+01, 1.32533333e+02, 3.40666667e+01,\n",
       "       3.56820000e+04, 5.99714286e+02])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the scaler stores the maximum values of the features, learned from train set\n",
    "\n",
    "scaler.data_max_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-3.44753865e-02, -1.96078431e-02, -6.42548386e-03, -9.88142292e-03,\n",
       "       -8.40830741e-05, -1.25216147e-03])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# tthe scaler stores the minimum values of the features, learned from train set\n",
    "\n",
    "scaler.min_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.45002000e+01, 5.10000000e+01, 1.31687179e+02, 3.37333333e+01,\n",
       "       3.56790000e+04, 5.98964286e+02])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# the scaler also stores the value range (max -  min)\n",
    "\n",
    "scaler.data_range_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedInc        0.000000\n",
       "HouseAge      0.000000\n",
       "AveRooms      0.004705\n",
       "AveBedrms     0.004941\n",
       "Population    0.000140\n",
       "AveOccup     -0.000096\n",
       "dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test_scaled.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MedInc        1.000000\n",
       "HouseAge      1.000000\n",
       "AveRooms      1.071197\n",
       "AveBedrms     0.750090\n",
       "Population    0.456907\n",
       "AveOccup      2.074553\n",
       "dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test_scaled.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams.update({\"font.size\": 15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test.hist(bins=20, figsize=(20, 12), layout=(2, 3))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x864 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X_test_scaled.hist(bins=20, figsize=(20, 12), layout=(2, 3))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsml",
   "language": "python",
   "name": "fsml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
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